A random-perturbation-based rank estimator of the number of factors

Biometrika ◽  
2020 ◽  
Author(s):  
Xinbing Kong
Keyword(s):  
Limit Theorem ◽  
Factor Model ◽  
Random Perturbation ◽  
Testing Procedure ◽  
Simulation Studies ◽  
Number Of Factors ◽  
Rank Estimator ◽  
Hypothesis Testing Procedure ◽  
Approximate Factor Model ◽  
New Hypothesis

Summary We introduce a random-perturbation-based rank estimator of the number of factors of a large-dimensional approximate factor model. An expansion of the rank estimator demonstrates that the random perturbation reduces the biases due to the persistence of the factor series and the dependence between the factor and error series. A central limit theorem for the rank estimator with convergence rate higher than root $n$ gives a new hypothesis-testing procedure for both one-sided and two-sided alternatives. Simulation studies verify the performance of the test.

scholarly journals A Test for the Number of Factors in an Approximate Factor Model

1993 ◽  
Vol 48 (4) ◽  
pp. 1263-1291 ◽  
Author(s):  
GREGORY CONNOR ◽  
ROBERT A. KORAJCZYK
Keyword(s):  
Factor Model ◽  
Number Of Factors ◽  
Approximate Factor Model

scholarly journals The Importance of the Human Factor in Safety for the Transport of Dangerous Goods

2021 ◽  
Vol 18 (14) ◽  
pp. 7525
Author(s):  
Sylwia Agata Bęczkowska ◽  
Iwona Grabarek
Keyword(s):  
Human Error ◽  
Human Factor ◽  
Factor Model ◽  
Heuristic Methods ◽  
Simulation Studies ◽  
Optimal Route ◽  
Human Actions ◽  
Dangerous Goods ◽  
Undesirable Event ◽  
Transport Of Dangerous Goods

This article discusses the issues related to the safety for the transport of dangerous goods by road. Research on accidents in transport unambiguously points to the human factor, which is the most responsible for causing accidents. Determining the causes of driver unreliability in the human−vehicle−environment system requires thorough research. Unfortunately, in this case, experimental research with human involvement is limited in scope. This leaves modeling and simulation of the behavior of the human factor, i.e., the driver transporting dangerous goods. The human being, because of its complexity, is a challenging element to parameterize. The literature presents various attempts to model human actions. Herein, the authors used heuristic methods, specifically fuzzy set techniques, to build a human factor model. In these models, human actions were specified using a verbal or linguistic description. The specificity of the fuzzy sets allowed for “naturally” limiting the “precision” in describing human behavior. The model was built based on the author’s questionnaire and expert research, based on which individual features were selected. Then, the traits were assigned appropriate states. The output parameter of the model was λL—the intensity of human error. The obtained values of the intensity of the accident caused by the driver’s error were implemented into the author’s method of risk assessment. They constituted one of the factors determining the probability of an accident in the transport of dangerous goods, which allowed for determining the optimal route for the transport of these goods characterized by the lowest risk of an undesirable event on the route. The article presents the model’s assumptions, structure, and the features included in the model, all of which have the most significant influence on shaping the intensity of human error. The results of the simulation studies showed a diversified effect of the analyzed characteristics on the driver’s efficiency.

Convergence or Divergence Patterns in Global Defence Spending: Further Evidence from a Nonlinear Single Factor Model

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Charles Shaaba Saba
Keyword(s):  
Low Income ◽  
Factor Model ◽  
National Income ◽  
Testing Procedure ◽  
Low Income Countries ◽  
Convergence Clubs ◽  
Defence Spending ◽  
Public Resources ◽  
World Income ◽  
International Convergence

AbstractThis study re-examines the international convergence in defence spending for 125 countries spanning 1985–2018. We employ the approach of Phillips and Sul, which tests for the existence of convergence clubs and the modelling of different transition paths to convergence. Our findings suggest no overall defence spending convergence at the world, income groups (except the low-income countries) and regional levels. However, we identify two convergence clubs using an iterative testing procedure and eventually (i) at world level, these two clubs exhibit convergence, and (ii) while taking into account Gross national income, geography and defence alliances/economic cooperation it is possible to make different number of convergence/divergence clubs. Contrary to previous findings, this study finds that the process of convergence in defence spending does not reflect the desirable emanations of defence policies sharing similar characteristics, at least in terms of the allocation of scarce public resources across the globe.

Determining the Number of Factors When Population Models Can Be Closely Approximated by Parsimonious Models

2021 ◽  
pp. 001316442199283
Author(s):  
Yan Xia
Keyword(s):  
Factor Model ◽  
Population Level ◽  
Parallel Analysis ◽  
Model Data ◽  
Behavioral Studies ◽  
Number Of Factors ◽  
Parsimonious Models ◽  
Parsimonious Model ◽  
Fit Index ◽  
Tucker Lewis Index

Despite the existence of many methods for determining the number of factors, none outperforms the others under every condition. This study compares traditional parallel analysis (TPA), revised parallel analysis (RPA), Kaiser’s rule, minimum average partial, sequential χ2, and sequential root mean square error of approximation, comparative fit index, and Tucker–Lewis index under a realistic scenario in behavioral studies, where researchers employ a closing–fitting parsimonious model with K factors to approximate a population model, leading to a trivial model-data misfit. Results show that while traditional and RPA both stand out when zero population-level misfits exist, the accuracy of RPA substantially deteriorates when a K-factor model can closely approximate the population. TPA is the least sensitive to trivial misfits and results in the highest accuracy across most simulation conditions. This study suggests the use of TPA for the investigated models. Results also imply that RPA requires further revision to accommodate a degree of model–data misfit that can be tolerated.

Non-random errors and their importance in testing of hypotheses

2021 ◽  
Vol 66 (3) ◽  
pp. 7-21
Author(s):  
Mirosław Szreder
Keyword(s):  
Statistical Tests ◽  
Testing Procedure ◽  
Random Errors ◽  
Sampling Errors ◽  
Wrong Decision ◽  
Contemporary Sample ◽  
Hypothesis Testing Procedure ◽  
Testing Of Hypotheses ◽  
Special Case ◽  
Classical Hypothesis

Increasing numbers of non-random errors are observed in contemporary sample surveying – in particular, those resulting from no response or faulty measutrements (imprecise statistical observation). Until recently, the consequences of these kinds of errors have not been widely discussed in the context of the testing of hypoteses. Researchers focused almost entirely on sampling errors (random errors), whose magnitude decreases as the size of the random sample grows. In consequence, researchers who often use samples of very large sizes tend to overlook the influence random and non-random errors have on the results of their study. The aim of this paper is to present how non-random errors can affect the decision-making process based on the classical hypothesis testing procedure. Particular attention is devoted to cases in which researchers manage samples of large sizes. The study proved the thesis that samples of large sizes cause statistical tests to be more sensitive to non-random errors. Systematic errors, as a special case of non-random errors, increase the probability of making the wrong decision to reject a true hypothesis as the sample size grows. Supplementing the testing of hypotheses with the analysis of confidence intervals may in this context provide substantive support for the researcher in drawing accurate inferences.

Integrating Voting Theory and Roll Call Analysis: A Framework

2003 ◽  
Vol 11 (4) ◽  
pp. 381-396 ◽  
Author(s):  
Joshua D. Clinton ◽  
Adam Meirowitz
Keyword(s):  
Ideal Point ◽  
Testing Procedure ◽  
Formal Modeling ◽  
Legislative Politics ◽  
Federal Aid ◽  
Voting Theory ◽  
Roll Call ◽  
Legislative Studies ◽  
Point Estimates ◽  
Hypothesis Testing Procedure

Scholars of legislative studies typically use ideal point estimates from scaling procedures to test theories of legislative politics. We contend that theory and methods may be better integrated by directly incorporating maintained and to be tested hypotheses in the statistical model used to estimate legislator preferences. In this view of theory and estimation, formal modeling (1) provides auxiliary assumptions that serve as constraints in the estimation process, and (2) generates testable predictions. The estimation and hypothesis testing procedure uses roll call data to evaluate the validity of theoretically derived to be tested hypotheses in a world where maintained hypotheses are presumed true. We articulate the approach using the language of statistical inference (both frequentist and Bayesian). The approach is demonstrated in analyses of the well-studied Powell amendment to the federal aid-to-education bill in the 84th House and the Compromise of 1790 in the 1st House.

Persepsi Masyarakat Mengenai Peranan Vegetasi Kawasan Sabuk Hijau Di Sempadan Sungai DAS Wae Batu Gajah

MAKILA ◽  
2019 ◽  
Vol 13 (1) ◽  
pp. 14-28
Author(s):  
Sitna Marasabessy ◽  
Bokiraiya Latuamury ◽  
Iskar Iskar ◽  
Christy C.V. Suhendy
Keyword(s):  
Formal Education ◽  
Open Space ◽  
Testing Procedure ◽  
Chi Square ◽  
Green Belt ◽  
Minimum Requirement ◽  
Environmentally Sustainable ◽  
Long Time ◽  
Hypothesis Testing Procedure ◽  
And Behavior

Green open space is at least a minimum requirement for an environmentally sustainable city at 30% of the total area. Pressure on green free space, especially the Green belt area in the river border, tends to increase from year to year due to an increase in urban population. Therefore, this study aims to analyze people's perceptions of the green belt vegetation's role in the watershed of the Wae Batu Gajah watershed in Ambon City. The research method uses descriptive methods that describe a situation based on facts in the field and do not treat the object, with the hypothesis testing procedure using Chi-Square. The results showed that the community's socio-economic parameters consisting of age, formal education, and occupation had a significant influence on the understanding of the green border of the river. In contrast, gender and marital status parameters have no significant effect on understanding the green belt border. Formal education can influence attitudes and behavior through values, character, and understanding of a problem built in stages in a person. The type of work a person has for a long time working will affect the environment's mindset and behavior. The poor only have two sources of income, through salaries / informal business surpluses for basic needs.

The hypothesis-testing procedure.

2009 ◽  
pp. 154-172
Author(s):  
George H. Weinberg ◽  
John A. Schumaker
Keyword(s):  
Hypothesis Testing ◽  
Testing Procedure ◽  
Hypothesis Testing Procedure

scholarly journals Assessing portfolio and asset returns of some financial and non- financial companies on the Ghana stock exchange using a 3-factor model

2021 ◽  
Vol 27 (2) ◽  
pp. 193-202
Author(s):  
C.P. Ogbogbo ◽  
N. Anokye-Turkson
Keyword(s):  
Factor Model ◽  
Stock Exchange ◽  
Asset Returns ◽  
Good Representation ◽  
Financial Firms ◽  
Number Of Factors ◽  
Equity Ratio ◽  
Book To Market Ratio ◽  
Ghana Stock Exchange ◽  
Market Volume

This study on the Ghana Stock Exchange (GSE), investigated, if the overall size of the market, affects the fundamentals of the Fama French 3-Factor model, and to ascertain if the Fama French model can be used effectively to assess portfolio and assets return for companies listed on the Ghana Stock Exchange. In this paper, portfolios of assets of companies on the Ghana Stock Exchange are constructed and analyzed using the Fama-French 3-factor model. The empirical data which consists of assets of 15 companies listed on the GSE, including assets of both financial and non-financial companies for good representation of the Ghana Stock Exchange. We found that the basic principle of the model is not satisfied. This is attributed to a number of factors which include overall size of the market, volume of trade, and high leverage (more debt than equity) associated with financial firms. High debt/equity ratio is linked to high risk. Keywords: Market Capitalization, Book-to-market ratio, Portfolio, Small minus big, High minus low

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